Pub Date : 2019-06-01DOI: 10.1109/YAC.2019.8787607
Yini Zhou, Hejin Xiong, Rui Zhang
Linear motor is widely used in industry and life because of its high precision, easy control and simple structure. The control strategy of linear motor has a direct impact on its speed and accuracy, so the research on its controller is of great significance. Considering the influence of environmental noise in the application of linear motor, this paper proposes a new fractional PID controller with fast response speed, small steady-state error and strong anti-noise interference ability.
{"title":"Research on new fractional PID control of linear motor","authors":"Yini Zhou, Hejin Xiong, Rui Zhang","doi":"10.1109/YAC.2019.8787607","DOIUrl":"https://doi.org/10.1109/YAC.2019.8787607","url":null,"abstract":"Linear motor is widely used in industry and life because of its high precision, easy control and simple structure. The control strategy of linear motor has a direct impact on its speed and accuracy, so the research on its controller is of great significance. Considering the influence of environmental noise in the application of linear motor, this paper proposes a new fractional PID controller with fast response speed, small steady-state error and strong anti-noise interference ability.","PeriodicalId":6669,"journal":{"name":"2019 34rd Youth Academic Annual Conference of Chinese Association of Automation (YAC)","volume":"1 1","pages":"38-41"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77651470","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The analysis and prediction of industrial production plants are of great significance for reducing energy consumption, improving economic efficiency. Therefore, a production prediction method based on bidirectional long short-term memory (Bi-LSTM) is proposed to accurately analyze and evaluate the energy efficiency status of ethylene production plants in industrial processes. Bi-LSTM is a Indirection ally connected network with two layers of long short-term memory (LSTM), it gives full consideration to the relationship between the current data and the data before and after it. Bi-LSTM solves the gradient disappearance or gradient explosion problem in recurrent neural network (RNN), and overcomes the drawback that LSTM only consider the relationship between the current data and its previous data. The comparison results show that the prediction effect of the Bi-LSTM model is superior to that of the back propagation (BP) neural network model, and the average relative error is reduced by 70%, which proves that the Bi-LSTM can effectively raise the accuracy and stability of the ethylene production prediction.
{"title":"Production prediction modeling of industrial processes based on Bi-LSTM","authors":"Yongming Han, Rundong Zhou, Zhiqiang Geng, Kai Chen, Yajie Wang, Qin Wei","doi":"10.1109/YAC.2019.8787713","DOIUrl":"https://doi.org/10.1109/YAC.2019.8787713","url":null,"abstract":"The analysis and prediction of industrial production plants are of great significance for reducing energy consumption, improving economic efficiency. Therefore, a production prediction method based on bidirectional long short-term memory (Bi-LSTM) is proposed to accurately analyze and evaluate the energy efficiency status of ethylene production plants in industrial processes. Bi-LSTM is a Indirection ally connected network with two layers of long short-term memory (LSTM), it gives full consideration to the relationship between the current data and the data before and after it. Bi-LSTM solves the gradient disappearance or gradient explosion problem in recurrent neural network (RNN), and overcomes the drawback that LSTM only consider the relationship between the current data and its previous data. The comparison results show that the prediction effect of the Bi-LSTM model is superior to that of the back propagation (BP) neural network model, and the average relative error is reduced by 70%, which proves that the Bi-LSTM can effectively raise the accuracy and stability of the ethylene production prediction.","PeriodicalId":6669,"journal":{"name":"2019 34rd Youth Academic Annual Conference of Chinese Association of Automation (YAC)","volume":"121 1","pages":"285-289"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78166711","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-01DOI: 10.1109/YAC.2019.8787609
Jingtao Shi
This paper deals with an optimal control problem of fully coupled forward-backward stochastic differential equations (FBSDEs), where the diffusion term does not contain the variable $z$ and the control domain is not necessarily convex. The connection among the adjoint variables and the value function is obtained in terms of the sub- and super-derivatives. It generalizes the result in [W. J. Meng, J. T. Shi, Connection between the adjoint variables and value function for controlled fully coupled FBSDEs: The local case, Proc. 15th International Conference on Control, Automation, Robotics and Vision, pp. 1263–1270, November 18–21, Singapore, 2018].
{"title":"Connection between the Adjoint Variables and Value Function for Controlled Fully Coupled FBSDEs: The Global Case","authors":"Jingtao Shi","doi":"10.1109/YAC.2019.8787609","DOIUrl":"https://doi.org/10.1109/YAC.2019.8787609","url":null,"abstract":"This paper deals with an optimal control problem of fully coupled forward-backward stochastic differential equations (FBSDEs), where the diffusion term does not contain the variable $z$ and the control domain is not necessarily convex. The connection among the adjoint variables and the value function is obtained in terms of the sub- and super-derivatives. It generalizes the result in [W. J. Meng, J. T. Shi, Connection between the adjoint variables and value function for controlled fully coupled FBSDEs: The local case, Proc. 15th International Conference on Control, Automation, Robotics and Vision, pp. 1263–1270, November 18–21, Singapore, 2018].","PeriodicalId":6669,"journal":{"name":"2019 34rd Youth Academic Annual Conference of Chinese Association of Automation (YAC)","volume":"7 1","pages":"617-624"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84918577","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-01DOI: 10.1109/YAC.2019.8787605
Qiujian Chen, Rong Long, Liyan Zhang
Due to the complexity of modeling water management system and difficulties of online measuring humidity inside the PEM fuel cell stack, the actor critic learning controller is proposed by using the available measurements which are stack voltage and the difference of stack voltage between current sample time and last sample time. In this method approximation of value function is based on least squares temporal-difference, and approximations of actor model and process model are based on local linear regression. Simulation results show that actor critic learning control can maintain water balance inside the fuel cell stack and achieve the maximum the stack voltage under the different operating conditions.
{"title":"Water Management in Proton Exchange Membrane Fuel Cell Based on Actor Critic Learning Control","authors":"Qiujian Chen, Rong Long, Liyan Zhang","doi":"10.1109/YAC.2019.8787605","DOIUrl":"https://doi.org/10.1109/YAC.2019.8787605","url":null,"abstract":"Due to the complexity of modeling water management system and difficulties of online measuring humidity inside the PEM fuel cell stack, the actor critic learning controller is proposed by using the available measurements which are stack voltage and the difference of stack voltage between current sample time and last sample time. In this method approximation of value function is based on least squares temporal-difference, and approximations of actor model and process model are based on local linear regression. Simulation results show that actor critic learning control can maintain water balance inside the fuel cell stack and achieve the maximum the stack voltage under the different operating conditions.","PeriodicalId":6669,"journal":{"name":"2019 34rd Youth Academic Annual Conference of Chinese Association of Automation (YAC)","volume":"285 1","pages":"250-254"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76868031","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-01DOI: 10.1109/YAC.2019.8787610
Xu Wang, Y. Du, Xufeng Liang
The carbon emissions trading scheme plays a significant role in promoting carbon emissions reduction. In this paper, the blockchain technology is applied to the carbon emission trading scheme, and the incentive mechanism of the reputation is added. A reputation-based carbon emission trading scheme (BCR-CETS) enabled by block chain is proposed. Compared with the traditional carbon emission trading scheme, it has the advantages of being safer and more efficient. In addition, case studies prove that BCR-CETS is more conducive to long-term carbon emission reduction.
{"title":"A Reputation-based Carbon Emissions Trading Scheme Enabled by Block Chain","authors":"Xu Wang, Y. Du, Xufeng Liang","doi":"10.1109/YAC.2019.8787610","DOIUrl":"https://doi.org/10.1109/YAC.2019.8787610","url":null,"abstract":"The carbon emissions trading scheme plays a significant role in promoting carbon emissions reduction. In this paper, the blockchain technology is applied to the carbon emission trading scheme, and the incentive mechanism of the reputation is added. A reputation-based carbon emission trading scheme (BCR-CETS) enabled by block chain is proposed. Compared with the traditional carbon emission trading scheme, it has the advantages of being safer and more efficient. In addition, case studies prove that BCR-CETS is more conducive to long-term carbon emission reduction.","PeriodicalId":6669,"journal":{"name":"2019 34rd Youth Academic Annual Conference of Chinese Association of Automation (YAC)","volume":"4 1","pages":"446-450"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73321685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-01DOI: 10.1109/YAC.2019.8787648
Peirui Zhao, Xiaohong Wang, Hongliang Yu, Shizeng Lu
The current of the main motor of the cement rotary kiln can represent the comprehensive situation in the kiln, which is a very important parameter. In this paper, the method for identifying the current operating conditions of the main motor of cement rotary kiln based on Spearman rank correlation coefficient is studied. Through the summary of expert experience, the kiln host current data template library is established, and the Spearman rank correlation coefficient algorithm is used to find the maximum similarity to realize the identification of the main motor drive current operating conditions. On this basis, combined with the expert experience, the rotary kiln temperature adjustment is given. rule. The experimental verification results show that according to the identified kiln main motor current operating conditions, the rotary kiln process parameters can be adjusted in real time, and the operating efficiency of the rotary kiln is improved.
{"title":"Method for Identifying Current Operating Conditions of Main Motor of Cement Rotary Kiln Based on Spearman Rank Correlation Coefficient","authors":"Peirui Zhao, Xiaohong Wang, Hongliang Yu, Shizeng Lu","doi":"10.1109/YAC.2019.8787648","DOIUrl":"https://doi.org/10.1109/YAC.2019.8787648","url":null,"abstract":"The current of the main motor of the cement rotary kiln can represent the comprehensive situation in the kiln, which is a very important parameter. In this paper, the method for identifying the current operating conditions of the main motor of cement rotary kiln based on Spearman rank correlation coefficient is studied. Through the summary of expert experience, the kiln host current data template library is established, and the Spearman rank correlation coefficient algorithm is used to find the maximum similarity to realize the identification of the main motor drive current operating conditions. On this basis, combined with the expert experience, the rotary kiln temperature adjustment is given. rule. The experimental verification results show that according to the identified kiln main motor current operating conditions, the rotary kiln process parameters can be adjusted in real time, and the operating efficiency of the rotary kiln is improved.","PeriodicalId":6669,"journal":{"name":"2019 34rd Youth Academic Annual Conference of Chinese Association of Automation (YAC)","volume":"25 1","pages":"537-541"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76012344","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-01DOI: 10.1109/YAC.2019.8787697
Na Zhan, Xi Wang, Bo Wei, Yuan Tao, Zhengyi Huang, Jiangwen Xiao
In the power system, most of the faults of disconnecting switch are eventually expressed as the form of heat. Therefore, we can detect the faults by observing its temperature. Most of the existing models employ conventional machine learning algorithms to learn the mapping function between temperature-related features and device temperature. These models do not make full use of the history information of the device to predict the current temperature value. However, in fact, the temperature variation of the disconnecting switch is continuous and sequential. In this paper, we propose a model based on Memory Regression Metric Learning (MRML) to predict the temperature of disconnecting switch. This model employs the historical features of the disconnecting switch together with a new feature for the temperature prediction, and uses metric learning to eliminate the impact of the data dimension. Experiments show that our model has better performance in temperature prediction than others.
{"title":"Temperature Prediction of Disconnecting Switch Based on Memory Regression Metric Learning","authors":"Na Zhan, Xi Wang, Bo Wei, Yuan Tao, Zhengyi Huang, Jiangwen Xiao","doi":"10.1109/YAC.2019.8787697","DOIUrl":"https://doi.org/10.1109/YAC.2019.8787697","url":null,"abstract":"In the power system, most of the faults of disconnecting switch are eventually expressed as the form of heat. Therefore, we can detect the faults by observing its temperature. Most of the existing models employ conventional machine learning algorithms to learn the mapping function between temperature-related features and device temperature. These models do not make full use of the history information of the device to predict the current temperature value. However, in fact, the temperature variation of the disconnecting switch is continuous and sequential. In this paper, we propose a model based on Memory Regression Metric Learning (MRML) to predict the temperature of disconnecting switch. This model employs the historical features of the disconnecting switch together with a new feature for the temperature prediction, and uses metric learning to eliminate the impact of the data dimension. Experiments show that our model has better performance in temperature prediction than others.","PeriodicalId":6669,"journal":{"name":"2019 34rd Youth Academic Annual Conference of Chinese Association of Automation (YAC)","volume":"128 1","pages":"206-210"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90605425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-01DOI: 10.1109/YAC.2019.8787655
Wang Geng
Big data has a revolutionary impact on the whole society, especially on the development of higher education. By investigating the current situation of academic evaluation of university students at home and abroad, this paper sorts out the relevant contents between big data and academic evaluation of university students, innovatively combines big data with academic evaluation of university students, aiming at promoting students' individualized development, making them grasp the principles of comprehensiveness, orientation, pluralism as well as difference, and exploring key connecting links and data sources in the process of developing academic evaluation. In order to bring the big data in students' academic evaluation into full play, this paper includes process design, data mining and realistic challenges.
{"title":"Research on Academic Evaluation of College Students Based on Big Data","authors":"Wang Geng","doi":"10.1109/YAC.2019.8787655","DOIUrl":"https://doi.org/10.1109/YAC.2019.8787655","url":null,"abstract":"Big data has a revolutionary impact on the whole society, especially on the development of higher education. By investigating the current situation of academic evaluation of university students at home and abroad, this paper sorts out the relevant contents between big data and academic evaluation of university students, innovatively combines big data with academic evaluation of university students, aiming at promoting students' individualized development, making them grasp the principles of comprehensiveness, orientation, pluralism as well as difference, and exploring key connecting links and data sources in the process of developing academic evaluation. In order to bring the big data in students' academic evaluation into full play, this paper includes process design, data mining and realistic challenges.","PeriodicalId":6669,"journal":{"name":"2019 34rd Youth Academic Annual Conference of Chinese Association of Automation (YAC)","volume":"23 20 1","pages":"85-89"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91259185","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This work aims to research mathematical properties of kinematic function for multi-joint robot, a Lyapunov function based method is presented to realize the robot joint angle control. Energy function is constructed based on the robot kinematic model and the stability of the PD controller is researched through invariant set theory, the simulation results prove that the control system has good dynamic performance according to step signal response.
{"title":"Research on Robot Position Control Based on Improved PD algorithm","authors":"Gao Guoyou, Jiang Chunsheng, Chen Tao, Hui Chun, Wu Lina, Liang Zifan","doi":"10.1109/YAC.2019.8787668","DOIUrl":"https://doi.org/10.1109/YAC.2019.8787668","url":null,"abstract":"This work aims to research mathematical properties of kinematic function for multi-joint robot, a Lyapunov function based method is presented to realize the robot joint angle control. Energy function is constructed based on the robot kinematic model and the stability of the PD controller is researched through invariant set theory, the simulation results prove that the control system has good dynamic performance according to step signal response.","PeriodicalId":6669,"journal":{"name":"2019 34rd Youth Academic Annual Conference of Chinese Association of Automation (YAC)","volume":"28 1","pages":"437-439"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76233158","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-01DOI: 10.1109/YAC.2019.8787657
Jingjing Zhai, Xiaobei Wu, Shaojie Zhu, Haoming Liu
Regional integrated energy system (RIES) can effectively improve the economy and environmental protection of terminal energy supply. In this paper, based on the discussion of the structure of typical RIES, multi-scenario fine modeling of key equipment is analyzed, then the probabilistic models of multiple loads of electricity, heat and cold are established. Scenario generation technology based on Latin hypercube sampling (LHS) in introduced, and scenario reduction technology based on K-means algorithm is carried out. After that, a low-carbon economic dispatching model of RIES considering load uncertainty is established, the costs of electricity, fuel, maintenance and carbon trading are considered, and energy balance constraints and several equipment operation constraints are taken into account. Case simulation results show that the low-carbon economic dispatching method of RIES proposed in this paper has obvious economic advantages compared with the traditional energy supply method. Considering the load uncertainty, the system will exchange smaller economy for higher stability. After joining the carbon emission market, the regional integrated energy system will consume more gas and buy less electricity, and the operation cost of the regional integrated energy system can be reduced obviously.
{"title":"Low Carbon Economic Dispatch of Regional Integrated Energy System Considering Load Uncertainty","authors":"Jingjing Zhai, Xiaobei Wu, Shaojie Zhu, Haoming Liu","doi":"10.1109/YAC.2019.8787657","DOIUrl":"https://doi.org/10.1109/YAC.2019.8787657","url":null,"abstract":"Regional integrated energy system (RIES) can effectively improve the economy and environmental protection of terminal energy supply. In this paper, based on the discussion of the structure of typical RIES, multi-scenario fine modeling of key equipment is analyzed, then the probabilistic models of multiple loads of electricity, heat and cold are established. Scenario generation technology based on Latin hypercube sampling (LHS) in introduced, and scenario reduction technology based on K-means algorithm is carried out. After that, a low-carbon economic dispatching model of RIES considering load uncertainty is established, the costs of electricity, fuel, maintenance and carbon trading are considered, and energy balance constraints and several equipment operation constraints are taken into account. Case simulation results show that the low-carbon economic dispatching method of RIES proposed in this paper has obvious economic advantages compared with the traditional energy supply method. Considering the load uncertainty, the system will exchange smaller economy for higher stability. After joining the carbon emission market, the regional integrated energy system will consume more gas and buy less electricity, and the operation cost of the regional integrated energy system can be reduced obviously.","PeriodicalId":6669,"journal":{"name":"2019 34rd Youth Academic Annual Conference of Chinese Association of Automation (YAC)","volume":"9 1","pages":"642-647"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74439348","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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